Migration Imaging Research Articles

Three methods of visco‐acoustic migration based on the De Wolf approximation and comparison of their migration images

AbstractThe viscosity of a medium affects the amplitude attenuation and velocity dispersion of seismic waves. Therefore, it is necessary to consider these factors during migration. First, to eliminate the viscous effect of a medium, we combine the Futterman model with the integral equation of the De Wolf approximation to construct a compensation operator of the De Wolf approximation for a visco‐acoustic medium. Next, we use the visco‐acoustic screen approximation method to realize the continuation operator then establish a prestack depth migration algorithm. Finally, an error analysis, impulse response test and model test are performed. The results show that three different generalized visco‐acoustic screen methods (phase screen method, generalized screen method and extended local Born Fourier method) can satisfactorily compensate for the attenuation of deep interface amplitude. Among these methods, the visco‐acoustic extended local Born Fourier method has the highest accuracy and the best compensation effect.

Improving reverse time migration of ground-penetrating radar under zero-time imaging conditions using cross-correlation superposition projection

ABSTRACT Aiming to address the issue of significant artefact interference in conventional reverse time migration (RTM) imaging under zero-time imaging conditions of ground-penetrating radar (GPR), this study proposes an improvement of RTM using cross-correlation superposition projection (CSP) to enhance imaging quality. The method is based on the original RTM imaging framework, where all single-trace signals are individually processed using RTM. The individual imaging results are then multiplied pairwise and added together to create a CSP. After normalizing the CSP and properly setting the adaptive threshold, the CSP can focus RTM imaging on the GPR signal reflection interface area, effectively removing artefact interference. Synthetic data test confirms that the CSP-improved RTM, when compared to conventional RTM and Laplace filtering methods, not only preserves all effective information in imaging but also eliminates artefact interference. This improvement significantly enhances the quality and resolution of the imaging results. Furthermore, the practicality and effectiveness of the CSP-improved RTM method in engineering applications have been validated using a set of measured GPR data.

Efficient Method for Enhancing Reverse-Time Migration Images Using Vertical Seismic Profiling Data

Vertical seismic profiling has garnered widespread attention in the industry as a supplement to seismic exploration due to its higher data quality compared to surface seismic data. However, its unique observation system in which geophones are only distributed within observation wells results in uneven coverage of subsurface structures. This can lead to significant noise when directly applying conventional reverse-time migration techniques used in surface seismic imaging. This study addresses the issue of noise suppression in reverse-time migration imaging associated with walk-away vertical seismic profiling and presents two main innovations. First, a common-receiver reverse-time migration imaging method is proposed, which uses the observation signals as excitation signals for the corresponding shots after reverse-time processing. Second, an excitation-time-constrained cross-correlation imaging condition is introduced to eliminate non-contributing portions of the wavefield, thereby modifying the traditional cross-correlation imaging condition to include an excitation time constraint. The combination of these methods enhances imaging quality by effectively suppressing noise, as demonstrated through theoretical analysis and numerical simulations with synthetic models.

An efficient illumination compensation method for reverse time migration

AbstractBy directly solving the full two‐way wave equation, reverse time migration has superiority over other imaging algorithms in handling steeply dipping structures and other complicated geological models. Moreover, by incorporating the asymptotic inversion operator into reverse time migration imaging condition, the imaging algorithm is able to give a quantitative estimation of parameter perturbation in high‐frequency approximation sense. However, because conventional asymptotic inversion only accounts for geometrical spreading, uneven illumination due to irregular acquisition geometry and inhomogeneous subsurface at each image point is neglected. The omit of illumination compensation significantly affects the imaging quality. Wave‐equation‐based illumination compensation methods have been extensively studied in the past. However, the traditional wave‐equation‐based illumination compensation methods usually require high computational cost and huge storage. In this paper, we propose an efficient wave‐equation‐based illumination compensation method. Under high‐frequency approximation, we first define a Jacobian determinant to measure the regularity of subsurface illumination, and then illumination compensation operators are proposed based on the Jacobian. Through boundary integration, we further express the illumination compensation operators through extrapolated wavefields; the explicit computation of asymptotic Green's functions is thus avoided, and an efficient illumination compensation implementation for reverse time migration is achieved. Numerical results with both synthetic and field data validate the effectiveness and efficiency of the presented method.

RETRACTION: Capn4 is a Marker of Poor Clinical Outcomes and Promotes Nasopharyngeal Carcinoma Metastasis via Nuclear Factor-κB-Induced Matrix Metalloproteinase 2 Expression.

P.-C. Zheng, X. Chen, H.-W. Zhu, W. Zheng, L.-H. Mao, C. Lin, J.-N. Liu and M. Zheng, "Capn4 is a Marker of Poor Clinical Outcomes and Promotes Nasopharyngeal Carcinoma Metastasis via Nuclear Factor-κB-Induced Matrix Metalloproteinase 2 Expression," Cancer Science 105, no. 6 (2014): 630-638, https://doi.org/10.1111/cas.12416. The above article, published online on 07 April 2014 in Wiley Online Library (wileyonlinelibrary.com), has been retracted by agreement between the journal Editor-in-Chief, Masanori Hatakeyama; Japanese Cancer Association; and John Wiley & Sons Australia, Ltd. Following publication, concerns were raised by a third party regarding suspected overlap of elements within the western blot presented in Figure3b and a figure published earlier in another paper elsewhere. Furthermore, image analysis uncovered several instances of overlap within the cell migration and cell invasion Transwell assay images presented in Figure3c. The authors were unable to provide the original data and did not provide a satisfactory explanation for the overlaps. As a result, the article's conclusions can no longer be considered valid.

A three-dimensional immersed boundary method for accurate simulation of acoustic wavefields with complex surface topography

Abstract Irregular topography of the free surface significantly affects seismic wavefield modelling, especially when employing finite-difference methods on rectangular grids. These methods represent the free surface as discrete points, resulting in a boundary that resembles a ‘staircase’. This approximation inaccurately represents surface topography, introducing errors in surface reflection traveltimes and generating artificial diffractions in wavefield simulation. We introduce a stable three-dimensional immersed boundary method (3DIBM) employing Cartesian coordinates to address these challenges. The 3DIBM enables the simulation of acoustic waves in media with complex topography through standard finite difference, extending the two-dimensional immersed boundary approach to compute spatial coordinates for ghost and mirror points in a three-dimensional space. Wavefield values at these points are obtained by three-dimensional spatial iterative symmetric interpolation, specifically through the Kaiser-windowed sinc method. By implicitly implementing the free surface boundary condition in three dimensions, this method effectively reduces artificial diffractions and enhances the accuracy of reflection traveltime. The effectiveness and accuracy of 3DIBM are validated through numerical tests and pre-stack depth migration imaging with simulated data, demonstrating its superiority as a modelling engine for migration imaging and waveform inversion in three-dimensional land seismic analysis.

Seismic modeling using pseudo-impedance derived from physical models

Building accurate numerical models of the earth for simulation is both challenging and time consuming. The subsurface complexity must be captured in sufficient detail for the results to be of practical use for geophysical analysis. Physical models provide an efficient way to add realistic detail to numerical models. Physical models, for example, are scaled simulations of large-scale geologic systems that provide great insight into understanding the interplay between sedimentation, salt tectonics, and faulting. The integration of geophysical workflows with sandbox models has been the subject of previous research, primarily to create synthetic data to compare with observed field data. However, capturing the detail from the physical model is challenging. A novel workflow is presented that uses pixel intensity values from photographic images of the analogue model to create a pseudo-impedance perturbation, mimicking the acoustic impedance contrasts that are encountered in the earth. This solution enables the detailed sedimentary architecture from the sandbox to be transferred to the digital earth model. Acoustic wave equation forward modeling and reverse time migration imaging have been applied using the generated pseudo-impedance model for a Gulf of Mexico-style salt canopy model. The images produced show clear definition of the salt/sediment interface and capture the sedimentary stratigraphy and faulting observed in the original sandbox model.

Optical flow vector of elastic waves in transversely isotropic media

The propagation direction of the wavefield is particularly important for migration imaging in the reverse-time migration (RTM) of elastic waves in transversely isotropic (TI) media. However, due to the problem of the computational instability of the Poynting vector, the wave field propagation direction estimated based on the Poynting vector method has errors and cannot accurately indicate the real propagation direction of the elastic wavefield. To solve this problem, a method for calculating the optical flow vector of elastic waves in TI media is developed to obtain the propagation direction. The optical flow vector of elastic waves in TI media is determined by applying the spatial and temporal derivatives of the wavefield at each time step under the assumption that the wavefields are almost the same at subsequent time steps and are smooth in the spatial direction. As the additional smoothing item is added and the multiple iterative algorithm is introduced in calculating the optical flow vector, the direction is calculated more accurately than the Poynting vector. Based on the optical flow vectors, we can separate the source wavefield and receiver wavefield into four directions: up-going, down-going, left-going, and right-going wavefields, respectively, and finally perform elastic reverse-time migration (ERTM) imaging based on the optical flow vector traveling-wave separation. We use a layered model and the BP model to test our method. The testing results demonstrate that the optical flow vector can overcome the Poynting vector limitations and obtain more accurate and reliable information regarding the direction of elastic wave propagation in TI media, as well as precisely separate the wavefields. The separated wavefields for migration effectively improve the quality of the ERTM.

Field application of near-borehole fracture acoustic imaging using a three-dimensional scanning inversion method

Borehole acoustic remote imaging can help identify and evaluate abnormal geological bodies within tens of meters of a well, which has a very important application prospect in fracture imaging. Compared to the borehole mode wave, the echo amplitude from a near-borehole fracture is considerably small, and the currently used wave field separation method cannot completely filter the borehole mode wave. Due to the influence of the large amplitude of the remaining borehole mode wave, several artifacts are often produced near the well when using traditional migration imaging. Thus, imaging and characterizing near-borehole fractures via acoustic imaging becomes difficult. To overcome this, we propose a three-dimensional scanning inversion method that attenuates the effects of remaining refracted waves on borehole acoustic imaging. We then perform data processing and imaging of field-logging data based on this method, and multimode echoes are used to identify and evaluate fractures. Finally, a comparison of the inversion results of the borehole acoustic and borehole electrical imaging showed that the three-dimensional scanning inversion method can effectively attenuate the remaining refracted wave and better realize the clear imaging of near-borehole fractures. Different modes of echoes illuminate different areas of fractures near wells. Therefore, based on scattered S-waves, the proposed imaging method can effectively detect fractures that cross-cut a well. Moreover, based on multimode waves, the method can suppress artifacts and highlight the azimuth characteristics of near-borehole fractures. Using the proposed method, high-precision positioning and fine characterization of formation fractures in near and far wells can be achieved simultaneously. Further, near-borehole fracture parameters—such as tendency, dip, and depth—can be inverted, and the results are consistent with the inversion results obtained through borehole electrical imaging. Thus, the proposed method enables the quantitative evaluation of near-borehole fractures.

A Displaced Lower Mantle Source of the Hainan Plume in South China Revealed by Receiver Function Imaging of the CEArray

AbstractWe analyzed 49,592 teleseismic receiver functions (RFs) recorded by 278 CEArray stations to image the mantle transition zone (MTZ) beneath the South China Block to understand the origins of deep velocity anomalies and their potential links to subduction and intraplate volcanism. We employed a fast‐marching method and a high‐resolution 3‐D velocity model (FWEA18) derived from full waveform inversion in computing P‐to‐S conversion times to better image the 410‐ and 660‐km discontinuities. Our results indicate that the common‐conversion‐point stacking of RFs using 3‐D conversion times yielded better migration images of the two discontinuities. The images revealed a slightly depressed 410‐km with a few small uplifted patches, and showed that the 660‐km beneath the western Yangtze Craton is depressed by 10–25 km, which is likely caused by the stagnant Paleo‐Pacific slab. The 660‐km beneath the southern Cathaysia Block has a 5–15 km high plateau with a topographic low at its central part. The lateral dimension of the topographic low is ∼150 km and is located beneath the central Pearl River Mount Basin near Hong Kong. We speculate that the topographic low occurs within the Hainan plume with a temperature excess of ∼300–400 K and is caused by the garnet phase transition. The displaced deep plume enters the MTZ and spreads nearly horizontally at the base. The plume evolves into two channels with a minor one toward the northeast and a major one toward the southwest, which keep moving upward to the 410‐km. The southwest channel is likely the source that feeds the Hainan volcanoes.

Depth imaging of multicomponent seismic data through the application of 2D full‐waveform inversion to P‐ and SH‐wave data: SEAM II Barrett model study

AbstractWe examine the value of the nine‐component seismic survey by generating the Kirchhoff depth migration images of compressional wave (P‐wave), converted wave (PS‐wave) and horizontally polarized shear wave (SH shear wave) data simulated from the SEAM II Barrett unconventional model. We first utilize full waveform inversion to obtain a P‐wave velocity model from P‐wave data and an S‐wave velocity model from SH‐wave data. Both P‐wave and SH‐wave data are generated with the maximum frequency of 20 Hz while assuming that the subsurface is isotropic. To implement full waveform inversion, we use a two‐dimensional time‐domain finite‐difference method and the L2 norm to measure the data misfit. We use both refractions and reflections in P‐ and SH‐wave data to reconstruct the P‐ and S‐wave velocity models from the surface to the reservoir. The inverted P‐ and S‐wave velocities contain the main features of the model (e.g., major faults and channels) but have some difficulties in estimating high‐frequency velocity variation within the first 300‐m depth of the model due to the frequency constraint. We then use the inverted P‐ and S‐wave velocities to generate Kirchhoff depth migration gathers and images from the P‐, PS‐ and SH‐wave data. The flat P‐ and SH‐wave common‐image offset gathers suggest that SH‐ and P‐wave full waveform inversion can generate adequate S‐ and P‐wave velocities for migration. Flat PS‐wave gathers and the clear PS‐wave migration image are also obtained using the inverted P‐ and S‐wave velocities simultaneously. This result indicates that obtaining S‐wave velocities from SH‐wave data can aid PS‐wave data processing and imaging. Moreover, the SH‐wave images and S‐wave images of the radial component provide better delineation of fault planes and small‐scale geobodies within the reservoir since the wavelength of the S‐wave is smaller compared to P‐wave when similar frequency ranges are recorded. Therefore, our study shows that S‐wave velocities can be successfully constructed by the two‐dimensional full waveform inversion application of the SH‐wave data. The subsequent imaging of multicomponent seismic data improves the delineation of certain unconventional reservoirs compared to the traditional P‐wave imaging.

Seismic Characterization of Subsurface Structures at Rock Valley, Nevada

ABSTRACT The Source Physics Experiment (SPE) aims at improving explosion monitoring techniques by investigating source characteristics of chemical explosions in geologic formations. One of the critical tasks in Rock Valley Direct Comparison (RV/DC), SPE phase III, is to prepare for the main experiment by characterizing the subsurface structures at the test site. Based on the seismic data acquired during an accelerated-weight-drop (AWD) seismic survey at Rock Valley, we first pick the P-wave first-arrival travel times and derive a P-wave velocity model using the adjoint-state first-arrival travel-time tomography. We then apply reverse-time migration to the processed seismic data and obtain high-resolution images of the subsurface structures along the two main survey lines. Our migration results show several reflectors corresponding to major geologic formation boundaries. We employ a multitask machine learning model to enhance the reverse-time migration images and identify faults from these images. We find that our automatically picked faults correlate well with the locations of known faults in the region in addition to many geologically undetected faults. Our subsurface characterization results refine our understanding of the geology in this region and provide valuable velocity and structural information for RV/DC geologic model building and fault identification.

Classification of traffic accidents’ factors using TrafficRiskClassifier

The TrafficRiskClassifier model introduced in this study adopts an innovative approach that incorporates migration learning, image classification, and self-supervised learning, aiming to significantly improve the accuracy and efficiency of traffic accident risk analysis. Compared with traditional traffic safety analysis techniques, this model focuses on utilizing contextual information and situational data of traffic accidents to achieve a higher level of risk classification accuracy. The core of this approach is to deeply mine and analyze the detailed information in the accident environment, to provide more scientific and effective support for traffic accident risk prevention and response. Initially, by integrating migration learning with image classification techniques, the model proficiently extracts pivotal features from intricate traffic scenarios and formulates initial assessments of accident risks. Subsequently, self-supervised learning is incorporated in this study, augmenting the model's capability to comprehend and categorize accident imagery. The TrafficRiskClassifier model exhibits a generalization ability of 91.82%, 85.16%, and 80.92% on individual classification tasks, respectively, signifying its robust learning capacity and proficiency in managing unseen data. Furthermore, the TrafficRiskClassifier model delineates a functional nexus between accident risk and variables such as weather, road conditions, and personal factors, employing a polynomial regression approach. This methodology not only amplifies the predictive precision of the model but also renders it versatile across diverse scenarios. Through the analysis of various polynomial functions, the model achieves enhanced accuracy in classifying disparate risk levels. The outcomes demonstrate that the TrafficRiskClassifier model can efficaciously amalgamate contextual information within traffic scenarios, thereby achieving more precise classification of traffic accident risks, and consequently serving as an invaluable instrument for urban traffic safety management.

Extraction of reflected waves from acoustic logging data using variation mode decomposition and curvelet transform

Remote reflection waves, essential for acquiring high-resolution images of geological structures beyond boreholes, often suffer contamination from strong direct mode waves propagating along the borehole. Consequently, the extraction of weak reflected waves becomes pivotal for optimizing migration image quality. This paper introduces a novel approach to extracting reflected waves by sequentially operating in the spatial frequency and curvelet domains. Using variation mode decomposition (VMD), single-channel spatial domain signals within the common offset gather are iteratively decomposed into high-wavenumber and low-wavenumber intrinsic mode functions (IMFs). The low-wavenumber IMF is then subtracted from the overall waveform to attenuate direct mode waves. Subsequently, the curvelet transform is employed to segregate upgoing and downgoing reflected waves within the filtered curvelet domain. As a result, direct mode waves are substantially suppressed, while the integrity of reflected waves is fully preserved. The efficacy of this approach is validated through processing synthetic and field data, underscoring its potential as a robust extraction technique.

Migration imaging processing of subgrade cavity GPR detection based on TUFK method

Migration imaging processing of subgrade cavity GPR detection based on TUFK method

Least-squares reverse time migration of simultaneous sources with deep-learning-based denoising

Least-squares reverse time migration (LSRTM) is currently one of the most advanced migration imaging techniques in the field of geophysics. It uses least-squares inversion to fit the observed data, resulting in high-resolution imaging results with more accurate amplitudes and better illumination compensation than conventional reverse time migration (RTM). However, noise in the observed data and the Born approximation forward operator can result in high-wavenumber artifacts in the final imaging results. Moreover, iteratively solving LSRTM leads to one or two orders of computational cost higher than conventional RTM, making it challenging to apply extensively in industrial applications. Simultaneous source acquisition technology can reduce the computational cost of LSRTM by reducing the number of wavefield simulations. However, this technique also can cause high-wavenumber crosstalk artifacts in the migration results. To effectively remove the high-wavenumber artifacts caused by these issues, simultaneous source and deep learning are combined to speed up LSRTM as well as suppress high-wavenumber artifacts. A deep residual neural network (DR-Unet) is trained with synthetic samples, which are generated by adding field noise to synthesized noise-free migration images. Then, the trained DR-Unet is applied on the gradient of LSRTM to remove high-wavenumber artifacts in each iteration. Compared to directly applying DR-Unet denoising to LSRTM results, embedding DR-Unet denoising into the inversion process can better preserve weak reflectors and improve denoising effects. Finally, the proposed LSRTM method is tested on two synthetic data sets and a land data set. The tests demonstrate that the proposed method can effectively remove high-wavenumber artifacts, improve imaging results, and accelerate convergence speed.

Viscoacoustic VTI media reverse time migration method in the complex-domain based on the staining algorithm

Underground media exhibit characteristics of viscosity and anisotropy, with vertical transversely isotropic (VTI) media being a common example of anisotropic media. Consequently, it is crucial to address the viscoacoustic VTI wave equation during forward modeling and migration imaging processes to attain highly precise imaging outcomes. However, conventional subsalt imaging techniques yield low accuracy and suffer from a low signal-to-noise ratio. To overcome this challenge, this study proposes a staining algorithm-based viscoacoustic vertical transversely isotropic reverse time migration (VTI RTM) in the complex-domain method by deriving the complex-domain viscoacoustic VTI equation. This method requires both the traditional real velocity field and the imaginary velocity field as inputs. The imaginary velocity field contains stained geological bodies and significant areas without data. Seismic waves propagate normally in the real wavefield, while in the imaginary wavefield, reflections occur only when the wavefront encounters stained geological bodies. The proposed method is assessed through testing on both a horizontally layered model and a salt model. Through comparative analysis, it has been verified that the method fully incorporates reflected waves with distinct structural features into the imaginary wavefield. Numerical experiments demonstrate that this method can accurately image subsalt structures.

Two‐dimensional SH‐wave and acoustic P‐wave full waveform inversion: A Midland Basin case study

AbstractBuilding a reliable S‐wave velocity model remains challenging from P‐wave land seismic data as multi‐parameter elastic full waveform inversion which updates P‐ and S‐wave velocities simultaneously is not yet widely adopted due to its computational cost, highly nonlinear nature and noise contamination from land seismic data. To overcome this challenge, we propose implementing the SH‐wave full waveform inversion to obtain the S‐wave velocity model. The value of this approach has been examined by applying two‐dimensional time‐domain SH‐ and P‐wave acoustic full waveform inversion to a nine‐component three‐dimensional seismic survey acquired in the Midland Basin. The nine‐component seismic survey was acquired by using both vertical and horizontal component vibrators and receivers, which enables us to apply both SH‐ and P‐wave full waveform inversion to the raw and preprocessed shot gathers along a two‐dimensional line. The SH‐ and P‐wave full waveform inversion applied to the raw shot gathers provide more detailed P‐ and S‐wave velocities compared to the velocities from the stacking velocity analysis. Additionally, there are no problematic artefacts in the inverted S‐wave velocity model, which shows the stability of the SH‐wave inversion. Through the SH‐wave full waveform inversion from the preprocessed shot gathers, we reveal the lateral velocity variations in the Grayburg–San Andres interval, which coincides with the depositional environment changes suggested by the previous regional study mainly based on well log and cores. These variations demonstrate that SH‐wave full waveform inversion can identify additional geological features that are not observed in the inverted P‐wave velocity model. The inverted P‐ and SH‐wave velocities are validated by the flattening of the events observed in the common image gathers after Kirchhoff depth migration. The SH‐wave migration image further reveals the irregular geometries of carbonates in the Spraberry formation. Vp/Vs ratios calculated from the independently inverted P‐ and S‐wave velocity models show strong lateral variations in the Wolfcamp interval (key‐producing interval), which could be caused by the organic content variations between the reservoir and non‐reservoir rocks. The inversion results demonstrate that the SH‐wave full waveform inversion can be used to provide an S‐wave velocity model that is comparable to the P‐wave velocity model derived from acoustic full waveform inversion, which is widely used for P‐wave velocity model building from P‐wave land seismic data.

An Application of 3D Cross-Well Elastic Reverse Time Migration Imaging Based on the Multi-Wave and Multi-Component Technique in Coastal Engineering Exploration

Precise surveys are indispensable in coastal engineering projects. The extensive presence of sand in the coastal area leads to significant attenuation of seismic waves within unsaturated loose sediments. As a result, it becomes challenging for seismic waves to penetrate the weathered zone and reach the desired depth with significant amount of energy. In this study, the application of three-dimensional (3D) cross-well elastic reverse time migration (RTM) imaging based on multi-wave and multi-component techniques in coastal engineering exploration is explored. Accurate decomposition of vector compressional (P) and shear (S) waves is achieved through two wavefield decoupling algorithms without any amplitude and phase distortion. Additionally, compressional wave pressure components are obtained, which facilitates subsequent independent imaging. This study discusses and analyzes the imaging results of four imaging strategies under cross-correlation imaging conditions in RTM imaging. The analysis leads to the conclusion that scalarizing vector wavefields imaging yields superior imaging of P- and S-waves. Furthermore, the imaging results obtained through this approach are of great physical significance. In order to validate the efficacy of this method in 3D geological structure imaging in coastal areas, RTM imaging experiments were performed on two representative models. The results indicate that the proposed 3D elastic wave imaging method effectively generates accurate 3D cross-well imaging of P- and S-waves. This method utilizes the multi-wave and multi-component elastic wave RTM imaging technique to effectively leverage the Earth’s elastic medium without increasing costs. It provides valuable information about the distribution of subsurface rock layers, interfaces, and other structures in coastal engineering projects. Importantly, this can be achieved without resorting to extensive excavation or drilling operations. This method addresses the limitations of current cross-well imaging techniques, thereby providing abundant and accurate geological and geophysical information for the analysis and interpretation of 3D geological structures in coastal engineering projects. It has important theoretical and practical significance in real-world production, as well as for the study of geological structures in coastal engineering.

Intraplate thrust orogeny of the Altai Mountains revealed by deep seismic reflection

The Altai orogen is a typical intracontinental orogen in Central Asia that experienced far-field deformation associated with Indian-Eurasian plate convergence. This region is characterized by uplift comparable to that of the Tianshan Mountains but has a distinct strain rate. Half of the Indo-Asia strain is accommodated by the Tianshan Mountains, whereas the Altai Mountains accommodates only 10%. To elucidate how the Altai Mountains produced such a large amount of uplift with only one-fifth of the strain rate of the Tianshan Mountains, we constructed a detailed crustal image of the Altai Mountains based on a new 166.8-km deep seismic reflection profile. The prestack migration images reveal an antiform within the Erqis crust, an ∼10 km Moho offset between the Altai arc and the East Junggar area, and a major south-dipping (30° dip) thrust in the lower crust beneath the Altai Mountains, which is connected to the Moho offset. The south-dipping thrust not only records the southward subduction of the Ob-Zaisan Ocean in the Paleozoic but also controlled the Altai deformation pattern in the Cenozoic with the Erqis antiform. The Erqis antiform prevented the extension of deformation to the Junggar crust. The south-dipping thrust in the lower crust of the Altai area caused extrusion of the lower crust, generating uplift at the surface, thickening of the crust, and steep (∼10 km) Moho deepening in the Altai Mountains. This process significantly widened the deformation zone of the Altai Mountains. These findings provide a new geodynamic model for describing how inherited crustal structure controls intraplate deformation without strong horizontal stress.